Deep integration of Python with Semantic Web technologies

Transcription

1 Deep integration of Python with Semantic Web technologies Marian Babik, Ladislav Hluchy Intelligent and Knowledge Technologies Group Institute of Informatics, SAS

2 Goals of the presentation Brief introduction of Semantic Web technologies Introduce deep integration ideas Show initial implementation of the Python integrated with OWL Discuss architecture

3 Semantic Web Extension of the current Web, providing infrastructure for the integration of data on the Web Data should be available for further processing It should be possible to combine and merge data on a Web scale Metadata, reasoning Making data machine processable: Names for resources Common data model: RDF Access to the data: SPARQL, OWL-QL Define vocabularies: RDFS, OWL, SKOS Reasoning: OWL, Rules

4 Resource Description Framework (RDF) Based on triples (subject, predicate, object) Labelled connection btw. two resources (subject, object) Subject, predicate are URI-s; Object is URI (e.g. Subject) or Literal ( ) (subject, predicate, object) can be seen as a labeled edge in a graph Serialization XML, Turtle, N3, etc.

5 RDF example Marian Babik s:hasname s:haswritten /Paper1.pdf Turtle (N3) XML/RDF <rdf:description rdf:about=" <s:hasname>marian Babik</s:hasName> <s:haswritten rdf:resource=" </rdf:description> < s:hasname Marian Babik ; s:haswritten <

6 RDF Vocabulary Description Language (RDFS) RDF lacks vocabulary with semantic meaning RDFS defines resources and classes and relationships among classes/resource rdf:type, rdfs:class, rdfs:subclassof rdfs:subpropertyof, Resource may belong to several classes (range, domain) Special kind of type system

7 RDFS example #Person rdf:type rdfs:subclassof #John rdf:type #Man :Person rdfs:subclassof :Man. :John rdf:type :Man. <rdf:description rdf:id= John > </rdf:description> <rdf:type rdf:resource= Man /> <rdf:description rdf:id= Man > <rdfs:subclassof rdf:resource= Person /> </rdf:description>

8 RDFS example (2) :Person rdfs:subclassof :Man. :John rdf:type :Man. :isprogrammer rdf:type rdf:property; rdf:domain :Person; rdf:range rdfs:literal.

9 Web Ontology Language (OWL) RDFS doesn t solve all the issues Reasoning about terms Behavior of properties (symmetric, transitive, etc.) Cardinality constraints Equivalence of classes Enumeration (oneof), union of classes Datatype properties Compromise btw Rich semantics Feasibility, implementability Three layers: OWL-Lite, OWL-DL (based on Description Logic SHOIN(D)) OWL-Full (might be undecidable)

10 OWL-DL Class definition, axioms Complex class definitions based on the class descriptions Property definition, axioms RDF Schema constructs (rdfs:subpropertyof, rdfs:domain and rdfs:range) relations to other properties: owl:equivalentproperty and owl:inverseof) global cardinality constraints: owl:functionalproperty and owl:inversefunctionalproperty logical property characteristics owl:symmetricproperty and owl:transitiveproperty Individuals facts about class membership and property values of individuals

11 OWL-DL people: < people:person a owl:class. people:man a owl:class; rdfs:subclassof people:person people:haschild a owl:property. people:hasson a owl:propery; rdfs:subpropertyof people:haschild PersonWithSingleSon a owl:class ; rdfs:subclassof [ a owl:restriction ; owl:cardinality "1"^^ ; owl:onproperty :hasson ]; rdfs:subclassof [ a owl:restriction ; owl:cardinality "1"^^ ; owl:onproperty :haschild ]. People:John a people:person. People:Bob a people:personwithsingleson.

12 SW for developers Classes are types for instances Each instance has one class (as its type). Classes don t share instances List of classes is known at compile time Compilers are used Properties are defined locally to a class Instances have values for attached properties. Values must be correctly typed. Range constraints are used for type checking Closed world assumption Class behavior through functions and methods Classes are sets of individuals Each individual can belong to multiple classes Classes can be created and changed at runtime Reasoners are used for classification and consistency Properties are standalone entities (can exist without classes) Instance can have arbitrary values for any property. Range and domain constraints can be used for type checking and type inference. Open world assumption Classes make their meaning explicit in terms of OWL statements. Source:

13 Deep integration ideas Import OWL classes alongside classes defined normally (native API) Support for intensional definition of classes/properties (OWL statements) Separation of concerns among declarative and procedural aspects Similar to what SQLObject does for databases

14 Benefits Ontologies Python Definition of data and domain using Semantic Web tools (Protégé, SWOOP) Native OWL API OWL Inference and Web sharing of concepts New programming paradigm for Python Native interface for ontologies, developers can work directly with OWL classes and their instances Existing Python Web frameworks and access to large set of libraries

15 OWL APIs Jena, OWL API Different notion of polymorphism means APIs have to introduce sophisticated design patterns Resource r = mymodel.getresource( myns + "DigitalCamera" ); OntClass cls = (OntClass) r.as( OntClass.class ); Restriction rest = (Restriction) cls.as( Restriction.class );

16 RDF/OWL APIs Python RDFLib statement-centric (Daniel Krech) CWM model centric Pychinko model, statement-centric, rule based MetaLog statement, resource-centric, based on prolog Sparta, Tramp resource centric Others Active RDF (Ruby) native mapping, RDF, integrated with Rails RDFHomepage (PHP) native mapping

17 OWL-DL and Python Ontology corresponds to Python module OWL Class corresponds to Python Class Instance of OWL Class corresponds to Python Object OWL Property corresponds to Python Class or Python method

18 Classes OWL Class corresponds to Python Class Instances of OWL Class correspond to Python Objects Class definition Each python class has two attributes: URI (owl:class URI) definedby (intensional definition) >>> from seth import Thing, Property >>> Person = Thing.new( :Person a owl:class.') >>> print Person <class seth.meta.person> >>> Man = Thing.new(' :Man a owl:class ; rdfs:subclassof :Person.')

19 Classes (2) >>> PersonWithSingleSon = Thing.new("""PersonWithSingleSon a owl:class ; rdfs:subclassof [ a owl:restriction ; owl:cardinality "1"^^ ; owl:onproperty :hasson ]; rdfs:subclassof [ a owl:restriction ; owl:cardinality "1"^^ ; owl:onproperty :haschild ].""") >>> model = OntModel() >>> model.bind( people, ) >>> Thing.setOntModel(model) >>> Person = Thing.new( people:person a owl:class. )

20 Properties owl:property corresponds to special kind of python object Similar to Class definition But such classes don t have instances >>> haschild = Property.new('hasChild a owl:objectproperty.') >>> print haschild <class 'seth.meta.haschild'> >>> hasson = Property.new('hasSon a owl:objectproperty ; rdfs:subpropertyof :haschild.') owl:property corresponds to python object attribute (method) >>> John.hasChild(Bob)

21 Individuals Individual is python object (class instance) >>> Bob = PersonWithSingleSon( Bob ) >>> John = Person('John ) >>> print John <seth.meta.person object at 0xb7a29e4c> >>> haschild(bob, John)

22 Ontologies owl:ontology corresponds to Python s module >>> ModuleFactory( people, ) >>> import people >>> print people.person <seth.people.person :Man a owl:class ; rdfs:subclassof :Person. >>> print people.john <seth.people.person object at 0xb7a29e4c> serialization >>> people.serialize( /tmp/test.owl, RDF/XML-ABBREV )

23 Queries Triple like queries >>> for individual in Person.findInstances():... print individual, individual.name <seth.meta.man object at 0xb7d0b64c> Peter <seth.meta.person object at 0xb7d0b50c> John <seth.meta.person object at 0xb7d0b6ec> Jane >>> for who in hasson.q(bob):... who.name 'John' >>> print hasson.query(bob, John) 1 OWL-QL, SPARQL Native queries

24 Architecture Interaction with Java-based libraries (reasoners) Interactive Class/Property Generators File/URI RDF/XML OntModel Knowledge Base Interface Query language Query Engine

25 Python and Java Jython - Python implemented for the Java Virtual Machine JPE(Java-Python Extension) - uses JNI to provide a bridging mechanism between Java and a Python interpreter JPype - interfacing at the native level in both Virtual Machines SPIRO - uses ORB (Object-Request Broker) technology GCJ

26 Issues Performance (conversion between JVMs) Cache Datatype properties Open world semantics Debugging Rules

27 Summary SETH Homepage: Available through CVS under MIT license Discussion, support mailing list: Contact:

28 References Introduction to Semantic Web Deep Integration Deep_Integration.pdf